Macrostate identification from biomolecular simulations through time series analysis
This paper builds upon the need for a more descriptive and accurate understanding of the landscape of intermolecular interactions, particularly those involving macromolecules such as proteins. For this, we need methods that move away from the single conformation description of binding events, toward...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/105296 http://hdl.handle.net/10220/17682 http://dx.doi.org/10.1021/ci300341v |
| _version_ | 1811680355344711680 |
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| author | Zhou, Weizhuang. Motakis, Efthimios. Fuentes, Gloria. Verma, Chandra S. |
| author2 | School of Biological Sciences |
| author_facet | School of Biological Sciences Zhou, Weizhuang. Motakis, Efthimios. Fuentes, Gloria. Verma, Chandra S. |
| author_sort | Zhou, Weizhuang. |
| collection | NTU |
| description | This paper builds upon the need for a more descriptive and accurate understanding of the landscape of intermolecular interactions, particularly those involving macromolecules such as proteins. For this, we need methods that move away from the single conformation description of binding events, toward a descriptive free energy landscape where different macrostates can coexist. Molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) methods provide an excellent approach for such a dynamic description of the binding events. An alternative to the standard method of the statistical reporting of such results is proposed. |
| first_indexed | 2024-10-01T03:23:44Z |
| format | Journal Article |
| id | ntu-10356/105296 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:23:44Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1052962019-12-06T21:48:52Z Macrostate identification from biomolecular simulations through time series analysis Zhou, Weizhuang. Motakis, Efthimios. Fuentes, Gloria. Verma, Chandra S. School of Biological Sciences DRNTU::Science::Biological sciences This paper builds upon the need for a more descriptive and accurate understanding of the landscape of intermolecular interactions, particularly those involving macromolecules such as proteins. For this, we need methods that move away from the single conformation description of binding events, toward a descriptive free energy landscape where different macrostates can coexist. Molecular dynamics simulations and molecular mechanics Poisson–Boltzmann surface area (MM-PBSA) methods provide an excellent approach for such a dynamic description of the binding events. An alternative to the standard method of the statistical reporting of such results is proposed. 2013-11-15T06:09:59Z 2019-12-06T21:48:52Z 2013-11-15T06:09:59Z 2019-12-06T21:48:52Z 2012 2012 Journal Article Zhou, W., Motakis, E., Fuentes, G., & Verma, C. S. (2012). Macrostate identification from biomolecular simulations through time series analysis. Journal of chemical information and modeling, 52(9), 2319-2324. https://hdl.handle.net/10356/105296 http://hdl.handle.net/10220/17682 http://dx.doi.org/10.1021/ci300341v en Journal of chemical information and modeling |
| spellingShingle | DRNTU::Science::Biological sciences Zhou, Weizhuang. Motakis, Efthimios. Fuentes, Gloria. Verma, Chandra S. Macrostate identification from biomolecular simulations through time series analysis |
| title | Macrostate identification from biomolecular simulations through time series analysis |
| title_full | Macrostate identification from biomolecular simulations through time series analysis |
| title_fullStr | Macrostate identification from biomolecular simulations through time series analysis |
| title_full_unstemmed | Macrostate identification from biomolecular simulations through time series analysis |
| title_short | Macrostate identification from biomolecular simulations through time series analysis |
| title_sort | macrostate identification from biomolecular simulations through time series analysis |
| topic | DRNTU::Science::Biological sciences |
| url | https://hdl.handle.net/10356/105296 http://hdl.handle.net/10220/17682 http://dx.doi.org/10.1021/ci300341v |
| work_keys_str_mv | AT zhouweizhuang macrostateidentificationfrombiomolecularsimulationsthroughtimeseriesanalysis AT motakisefthimios macrostateidentificationfrombiomolecularsimulationsthroughtimeseriesanalysis AT fuentesgloria macrostateidentificationfrombiomolecularsimulationsthroughtimeseriesanalysis AT vermachandras macrostateidentificationfrombiomolecularsimulationsthroughtimeseriesanalysis |